1. Field of the Invention
The present invention is directed to the identification of recordings and, more particularly, to the identification of sound recordings, such as recordings of music or spoken words.
2. Description of the Related Art
Identification is a process by which a copy of a sound recording is recognized as being the same as the original or reference recording. There is a need to automatically identify sound recordings for the purposes of registration, monitoring and control, all of which are important in ensuring the financial compensation of the rights owners and creators of music. There is also a need for identification for the purposes of adding value to, or extracting value from the music. Registration is a process by which the owner of content records his or her ownership. Monitoring records the movement and use of content so that it can be reported back to the owner, generally for purposes of payment. Control is a process by which the wishes of a content owner regarding the use and movement of the content are enforced.
Some examples of adding value to music include: identification of unlabelled or mislabeled content to make it easier for users of the music to access and organize their music and identification so that the user can be provided with related content, for example, information about the artist, or recommendations of similar pieces of music.
Some examples of extracting value from music include: identification for the provision of buying opportunities and identification for the purpose of interpreting something about the psychographics of the listener. For example, a particular song may trigger an offer to purchase it, or a related song by the same artist, or an article of clothing made popular by that artist. This extracts value from the music by using it as a delivery vehicle for a commercial message. In addition, psychographics uses psychological, sociological and anthropological factors to determine how a market is segmented by the propensity of groups within the market to make a decision about a product, person, ideology or otherwise hold an attitude or use a medium. This information can be used to better focus commercial messages and opportunities. This extracts value from the music by using it to profile the listener.
There have been two types of monitoring, reflecting the delivery of stored music and the delivery of played music. Stored music is considered to be copies for which there are “mechanical” or “reproduction” rights. Played music may be considered to be a performance, whether or not the performance is live or recorded. This demarcation is reflected in different payment structures, which are administered by different organizations. One organization (Harry Fox Agency) collects reproduction royalties when CDs or tapes are sold. These physical goods are counted and monitored using a variety of accounting practices and techniques. ASCAP, BMI and SESAC collect performance royalties when live or recorded music is played on the radio or in public spaces. These performances are monitored using a combination of automatic identification methods and human verification.
There are several different methods used for delivery of music. Live music is “delivered” in a performance space, by radio and TV (both analog and digital) and over the Internet. Stored music or other sound recordings may be delivered on physical media associated with the recordings (CDs, cassettes, mini discs, OD-RWs, DVDs) which may be moved (stored, distributed, sold, etc). However, a sound recording does not have to be associated with a physical medium; it can also be easily transported in electronic form by streaming, or by moving from one storage location to another. In both cases, either radio or the Internet may be used to transport the sound recording.
Digital music and the Internet are changing the way music is delivered and used, and are changing the requirements for music identification. These changes are brought about because the Internet can be used to deliver both performances and copies, and the Internet increases the number of delivery channels.
Whereas a terrestrial radio station may reach one thousand listeners at any moment in time while playing the same one song, an Internet radio station may reach one thousand listeners at one time while playing one thousand different songs. This means that a larger and more diverse selection of songs must be identified.
Existing business models for music are being challenged. For example, CD readers attached to personal computers, and peer-to-peer services are making it easier to copy and exchange music. New methods for registering, monitoring, controlling, and extracting value from music are needed.
The copying of digital music is easy. Users are able to make copies on a variety of different media formats, for a variety of consumer electronic devices. This creates a need to identify more copies of songs, across multiple media formats and types of device. Some of the devices are not connected to the Internet, which introduces an additional requirement on an identification system.
There is a need for a single solution that can identify streamed or moved music across all delivery channels. A single solution is preferable due to economies of scale, to remove the need to reconcile across methods and databases, and to provide a simple solution for all aspects of the problem.
Current methods rely on attaching tags, watermarks, encryption, and fingerprints (the use of intrinsic features of the music). Tags are attached to the physical media or to the digital copy. The lowest common denominator is the artist-title pair (ATP). Other information can include publisher, label and date. Attempts to give a sound recoding a unique ID include the ISRC (International Standard Recording Code), the ISWC (International Standard Work Code), the EAN (European Article Number), the UPC (Universal Product Code), ISMN (International Standard Music Number) and the CAE (Compositeur, Auteur, Editeur). All are alphanumeric codes that are either attached to physical copies of the sound recording, or embedded in the digital copy. Part of the rationale for creating the various codes was to assist with the automated identification and tracking of the works.
However, there are problems with the use of ATPs and alpha-numeric codes. They can be easily detached or changed (as evidenced by the recent attempts by Napster to use ATPs to block content). Once detached or changed, they require human intervention (listening) to be reattached or corrected. There is no way to automatically authenticate that the content is what it's tag claims it to be. They must be attached at source, prior to duplication, which reduces their utility with legacy content. They are applied intermittently or incorrectly. They require a critical mass of industry participants to be useful. EAN/UPC identify the CD and are not useful for individual music tracks. In some countries, there are laws against transmitting data along with the music, which limits their utility. Also, transmitting such data may require additional bandwidth.
Watermarks add an indelible and inaudible signal that is interpreted by a special reader. Watermarks can be robust to noise. They are good for combinations of live and recorded content, for example where an announcer speaks over recorded background music. Watermarks can deliver additional information without the need to access a database. The problems with watermarks are: they are not necessarily indelible nor inaudible; they require addition at source, prior to duplication, and therefore have limited utility for legacy content; and if applied to legacy content, there still needs to be a way to first identify the music.
Encryption uses techniques embedded in software to make the content inaccessible without a key. Identification is done prior to encryption, and the identification information (metadata) is locked up with the music. Some of the problems with encryption are: it has limited utility for legacy content, if applied to legacy content, there still needs to be a way to identify that content; and there is consumer resistance to locking up music. These problems are caused by incompatibilities between equipment that plays locked music and equipment that does not, leading to a reluctance to purchase equipment that may not play their existing music collections and to purchasing music that may not play on equipment the consumers currently own.
Another approach is to use intrinsic properties of the music to provide a “fingerprint.”The identifying features are a part of the music, therefore changing them changes the music. The advantages of this method include: nothing is added to the music; the fingerprints can be regenerated at any time; fingerprints work on legacy content and do not require broad industry adoption to be applicable to all content; and fingerprints can made of an entire song, and can therefore ensure that song's completeness and authenticity.
Current fingerprinting methods are not suitable, for reasons that will be described in more detail later. Their limitations come about because of the requirements for (1) identifying large numbers of songs, and (2) identifying songs that have slight variations from the original. These variations are insufficient to cause a human to judge the songs as being different, but they can be sufficient to cause a machine to do so. In sum, the problems with current fingerprinting methods are that some systems can handle a large number of songs, but cannot handle the variations, while other systems can handle many variations, but cannot handle a large number of songs.
Variations in songs may be caused by numerous “delivery channel effects.” For example, songs played on the radio are subjected to both static and dynamic frequency equalization and volume normalization. Songs may also be speeded up or slowed down to shorten or lengthen their playing time. Stored music can vary from the original because of the same effects found in radio, and because of other manipulations. The most common manipulation is the use of a codec to reduce the size of a file of stored music to make it more suitable for storage or movement. The most common codec is the MP3. The codec encodes the song to a compressed form, and at playback decodes, or expands, it for listening. An ideal codec will remove only those parts of the original that are minimally perceptually salient so that the version that has undergone compression and expansion sounds like the original. However, the process is lossy and changes the waveform of the copy from that of the original. Other manipulations and their manifestations (delivery channel effects) are described below.
Existing methods are intended for identifying stored sound recordings, and for identifying sound recordings as they are being played (performances). The main distinctions between the two identification systems are:    Played music identification systems must be capable of identifying a song without any knowledge of the song's start point. It is easier to find the start point in stored music.    Played music identification can have an upper capacity of about 10,000 reference recordings. Stored music requires a larger capacity.    Played music is identified as it is being played, so there is not a stringent requirement for speed of fingerprint extraction or lookup. For many applications, stored music must be identified at many times real time.    Played music identification may be limited to several thousand radio stations. There is a need for stored music identification by tens of millions of individual music users.    Played music must be identified in the presence of manipulations that create variations from the original. Methods of identifying stored music in the prior art are not designed to compensate for variations.
Both categories include techniques that rely on the use of intrinsic properties, the addition of metadata or the addition of inaudible signals. However the examination will concentrate on those identification techniques that use the intrinsic properties of the sound recording, either by themselves, or in combination with other information.
One commonly used technique for identifying copies of music on a compact disc (CD) is to use the spacing between tracks and the duration of tracks or the “Table of Contents” of a CD to create a unique identifier for the CD, as described in U.S. Pat. No. 6,230,192. The CD identity is used to lookup the name and order of the tracks from a previously completed database. This method does not work once the music has been removed from the CD, and is a copy on a computer hard drive.
Another technique uses a hash algorithm to label a file. Hash algorithms, such as the Secure Hash Algorithm (SHA1) or MD5, are meant for digital signature applications where a large message has to be “compressed” in a secure manner before being signed with the private key. The algorithms may be applied to a music file of arbitrary length to produce a 128-bit message digest. The benefits of the hash values are they are quick to extract, they are small in size, and they can be used to perform rapid database searches because each hash is a unique identifier for a file. The disadvantages include:    (1) The algorithms are designed to be secure to tampering, so any change to the file, however minor, will result in a different hash value. As a result, the hash value changes when the file is subjected to any of the channel effects. For example, there are on average 550 variants of each song on a large file sharing exchange such as Napster. A slight alteration of a song (e.g. the removal of one sample) will result in a different hash, which will not be able to be used to identify the song.    (2) Each variant of a song file requires that a different hash be stored in the database, resulting in a large database with a many-to-one relationship.
Yet another technique is described in U.S. Pat. No. 5,918,223. The method extracts a series of feature vectors from a piece of music which it then sends to a database for identification. The advantages of this technique are that the feature vectors consist of intrinsic properties of music that are claimed to be perceptually salient. This means that they should be robust to many of the distribution channel effects. The disadvantages are:    (1) The feature vector is computationally intensive to extract    (2) The feature vector is large, which means:            (a) It takes long time to look up and is expensive to implement for large numbers of queries.        (b) It increases the amount of network traffic            (3) Each individual vector does not contain sufficient information to uniquely identify a song. Identification is accomplished after a series of feature vectors are matched in the database. The database therefore takes a long time to search and must be limited in size.    (4) There is no evidence that the technique is immune to all delivery channel effects.
One method for identifying played sound recordings is described by Kenyon in U.S. Pat. No. 5,210,820. The '820 patent is primarily designed for radio station monitoring where the signal is acquired from listening stations tuned to a terrestrial radio station of interest. The system is capable of identifying songs irrespective of speed variation, noise bursts, and signal dropout. It is capable of monitoring for one of approximately 10,000 songs in each of 5 radio channels. The disclosed technique is fairly robust, but the size of the database of reference songs is limited, primarily due to the database search techniques used.
Identifying all sound recordings includes stored music for around 10 million different songs in early 2002. For streamed music this number is in the tens of thousands. The prior art has focused on streamed music with a much smaller number of songs.
Identifying legacy content applies to approximately 500 billion copies of digital music in existence. Methods that require the music to be identified at the point of origin cannot identify these copies.
New content consists of relatively few songs that comprise the majority of popular music, distributed from a few points of origin, with processes in place to control the workflow, plus a larger number of songs distributed from many points of origin. These points are geographically distributed, and have diverse methods of workflow management. Therefore, methods that require the music to be identified at the point of origin cannot identify the majority of songs.